Metadata-Version: 2.1
Name: easydecon
Version: 0.1.0a0
Summary: easydecon
Home-page: https://github.com/sinanugur/easydecon
Author: Sinan U. Umu
Author-email: sinanugur@gmail.com
Keywords: scRNA single-cell high definition spatial transcriptomics deconvolution
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: scipy
Requires-Dist: regex
Requires-Dist: matplotlib
Requires-Dist: pandas==2.2.2
Requires-Dist: numpy
Requires-Dist: stardist
Requires-Dist: spatialdata==0.2.2
Requires-Dist: spatialdata-io==0.1.4
Requires-Dist: spatialdata-plot==0.2.4
Requires-Dist: xarray-spatial==0.4.0
Requires-Dist: ipykernel
Requires-Dist: squidpy
Requires-Dist: joblib
Requires-Dist: napari
Requires-Dist: napari-spatialdata
Requires-Dist: napari[pyqt6_experimental]
Requires-Dist: xlrd==2.0.1

# Easydecon

A package to analyze celltypes on high definition spatial profiling assays

Installation
------------
It is recommended to install the package in a virtual environment or a Conda environment. To create a Conda environment, run the following command:

```bash
conda create -n easydecon python=3.11
conda activate easydecon
```

To install directly from GitHub using pip into the active environment, run the following command:

```bash
pip install git+https://github.com/sinanugur/easydecon.git
```


Usage and Documentation
-----------------------
You may find our example notebooks in the `notebooks` folder.

- Demo notebook for a single-cell Anndata object (demo)[https://github.com/sinanugur/easydecon/blob/main/notebooks/demo.ipynb]
- Demo notebook for macrophage markers (demo_macrophage)[https://github.com/sinanugur/easydecon/blob/main/notebooks/demo_macrophage.ipynb]
